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Enriching textbooks with images
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Worker types and personality traits in crowdsourcing relevance labels
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Shepherding the crowd yields better work
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Micro perceptual human computation for visual tasks
ACM Transactions on Graphics (TOG)
On the institutional archiving of social media
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Predicting qos in scheduled crowdsourcing
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Pushing the limits of mechanical turk: qualifying the crowd for video geo-location
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GeoCrowd: enabling query answering with spatial crowdsourcing
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Enhancing reliability using peer consistency evaluation in human computation
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Patterns for visualization evaluation
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How to filter out random clickers in a crowdsourcing-based study?
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WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
An analysis of human factors and label accuracy in crowdsourcing relevance judgments
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A pilot study of using crowds in the classroom
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Analyzing crowd workers in mobile pay-for-answer q&a
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Turkopticon: interrupting worker invisibility in amazon mechanical turk
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Labor dynamics in a mobile micro-task market
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Statistical quality estimation for general crowdsourcing tasks
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Adaptive crowdsourcing for temporal crowds
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From sensing to controlling: the state of the art in ubiquitous crowdsourcing
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Human vs machine: establishing a human baseline for multimodal location estimation
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Query optimization over crowdsourced data
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A reputation management approach for resource constrained trustee agents
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Lifelong learning for acquiring the wisdom of the crowd
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Community-based bayesian aggregation models for crowdsourcing
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The wisdom of minority: discovering and targeting the right group of workers for crowdsourcing
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World Wide Web
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An associate professor at New York Universitys Stern School of Business uncovers answers about who are the employers in paid crowdsourcing, what tasks they post, and how much they pay.